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Comparison of time series from ecosystems and an artificial multi-agent network based on complexity measures

Title data

Hauhs, Michael ; Koch, Jennifer ; Lange, Holger:
Comparison of time series from ecosystems and an artificial multi-agent network based on complexity measures.
In: Kim, J.T. (Hrsg.): Systems Biology Workshop at the VIIIth European Conference on Artificial Life. - Canterbury , 2005

Abstract in another language

We investigate ecosystem dynamics by analyzing time series of measured variables. The information content and the complexity of these data are quanti ed by methods from information theory. When applied to runoff (stream discharge) from catchments, the information/complexity relation reveals a simple non-trivial property for a large ensemble (more than 1800) of time series. This behaviour is so far not understood in hydrology. Using a multi-agent network receiving input resembling rainfall and producing output, we are able to reproduce the observed behaviour for the first time. The reconstruction is based on the identification and subsequent replacement of general patterns in the input. We thus consider runoff dynamics as the expression of an interactive learning problem of agents in an ecosystem.Keywords: Artificial life; time series; complexity

Further data

Item Type: Article in a book
Refereed: No
Additional notes: BAYCEER30136
Institutions of the University: Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Earth Sciences > Chair Ecological Modelling
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Earth Sciences > Chair Ecological Modelling > Chair Ecological Modelling - Univ.-Prof. Dr. Michael Hauhs
Research Institutions > Research Centres > Bayreuth Center of Ecology and Environmental Research- BayCEER
Faculties
Faculties > Faculty of Biology, Chemistry and Earth Sciences
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Earth Sciences
Research Institutions
Research Institutions > Research Centres
Result of work at the UBT: Yes
DDC Subjects: 500 Science
Date Deposited: 06 Jul 2015 10:25
Last Modified: 06 Jul 2015 10:25
URI: https://eref.uni-bayreuth.de/id/eprint/15973